Field of the Invention
Embodiments of the invention generally relate to a situational awareness analysis and fatigue management system that includes a processor specifically configured to perform dynamic assessment of situational awareness (DASA) and identify situational awareness longevity conditions of a user, forecast advanced fatigue conditions of the user, and improve situational awareness performance of the user to perform a task. One or more embodiments may calculate one or more bio-inertia or “binertia” lines based on the response pitch time (RTP) of the user as a change in the user's response time per hour of wakefulness indicative of the user's longevity of effective performance. The binertia lines may be plotted for example as a function of the Response Wake Time (RWT) and RTP, on a dynamic psychomotor vigilance test (D-PVT) diagram to show performance regions indicative of best, good, poor or other regions related to effective performance. Specifically, but not by way of limitation, the system assesses the user's qualitative level of situational awareness across the user's wakefulness time, forecasts the time when the user may most likely experience the onset of fatigue, enables safer task scheduling, can be utilized in accident reconstruction efforts, for example aviation or public transportation accidents and can be utilized to increase the user's situational awareness capability and longevity to improve safety including safety in any endeavor, for example aviation safety.
Description of the Related Art
Generally, a variety of professions require “on duty” working hours for a certain amount of time or schedule including day shifts, night shifts, or both. Typically, extended periods of working hours may lead to fatigue and therefrom affecting a worker's alertness, awareness and performance. For example, insufficient sleep may lead to unsafe conduct during on duty hours due to sleep deprivation, leading to a higher risk of accidents.
Typically, maintaining performance and awareness during working hours relies on sleep behavior, time of day, wakefulness, perception, and other cognitive performance factors. Fatigued workers, generally, results in disorientation and loss of performance that may correlate with loss of performance from blood alcohol content. For example, pilots in charge of evening trip assignments without routinely monitoring their sleep behavior and wakefulness hours prior to the trips may lead to unsafe behavior affecting the pilot and personnel on board. With pilots crossing multiple time zones and sleeping at odd hours for inconsistent durations, this may cause dangerous levels of fatigue.
Generally, fatigue management systems rely mostly only on a user's sleep history to rate the user's cognitive performance
United States Patent Publication 20120065893, to Lee, entitled “Method and Apparatus for Mitigating Aviation Risk by Determining Cognitive Effectiveness From Sleep History”, describes a method and apparatus for managing fatigue. The system of Lee relies on sleep quantity, quality and interruptions, and outputs a user's cognitive effectiveness therefrom ranging from high to low. However, the system of Lee appears to lack any mention of accepting, a plurality of groups of user input data, calculating a user's response time to a series of tests, generating a set of algorithms therefrom, and forecasting advanced fatigue conditions and user situational awareness for a specific task.
U.S. Pat. No. 7,766,827, to Balkin et al., entitled “Method and System for Predicting Human Cognitive Performance”, describes predicting cognitive performance of an individual using sleep history and time of day, and reconstructing past cognitive performance levels based on sleep history. However, the system of Balkin et al. appears to lack any mention of accepting, a plurality of groups of user input data, calculating a user's response time to a series of tests, generating a set of algorithms therefrom, and forecasting advanced fatigue conditions and user situational awareness for a specific task.
For example, United States Patent Publication 20030018242, to Hursh et al., entitled “Interface for a System and Method for Evaluating Task Effectiveness Based on Sleep Pattern”, describes an interface for evaluating effectiveness of a person to perform a task based on sleep. According to Hursh et al., the results may be correlated to sunlight in the user's location, and may account for changes in the users location, sunlight during the user's sleep cycle, and other schedule modifying events. However, the system of Hursh et al. appears to lack any mention of accepting, a plurality of groups of user input data, calculating a user's response time to a series of tests, generating a set of algorithms therefrom, and forecasting advanced fatigue conditions and user situational awareness for a specific task.
United States Patent Publication 20060200008, to Moore-Ede, entitled “Systems and Methods for Assessing Equipment Operator Fatigue and Using Fatigue-Risk-Informed. Safety-Performance-Based Systems and Methods to Replace or Supplement Prescriptive Work-Rest Regulations”, describes a system and method to assess and modify fatigue based on current worst-rest pattern and/or sleep data from an individual. The system of Moore-Ede combines the data to generate a fatigue assessment result, a diagnostic result and a corrective intervention result. However, the system of Moore-Ede appears to lack any mention of accepting, a plurality of groups of user input data, calculating a user's response time to a series of tests, generating a set of algorithms therefrom, and forecasting advanced fatigue conditions and user situational awareness for a specific task.
For example, U.S. Pat. No. 7,621,871, to Downs, entitled “Systems and Methods for Monitoring and Evaluating Individual Performance”, describes a system for monitoring and evaluating cognitive effectiveness using a portable monitoring device that collects data from a user. However, the system of Downs appears to lack any mention of accepting, a plurality of groups of user input data, calculating a user's response time to a series of tests, generating a set of algorithms therefrom, and forecasting advanced fatigue conditions and user situational awareness for a specific task.
Therefore, in view of the above, there is a need for a system and method to determine and manage a user's situational awareness using a plurality of groups of user input data in addition to sleep patterns, and a plurality of tests and algorithms to forecast advanced fatigue conditions.